child_mortality
## # A tibble: 44,926 x 10
##     year country continent population child_mort survival_per_wo~
##    <int> <chr>   <chr>          <int>      <dbl>            <dbl>
##  1  1957 Afghan~ Asia         9147286       378.             4.75
##  2  1958 Afghan~ Asia         9314915       372.             4.80
##  3  1959 Afghan~ Asia         9489453       366.             4.85
##  4  1960 Afghan~ Asia         9671046       361.             4.89
##  5  1961 Afghan~ Asia         9859928       355.             4.94
##  6  1962 Afghan~ Asia        10056480       350.             4.98
##  7  1963 Afghan~ Asia        10261254       344.             5.02
##  8  1964 Afghan~ Asia        10474903       339.             5.07
##  9  1965 Afghan~ Asia        10697983       334.             5.11
## 10  1966 Afghan~ Asia        10927724       329.             5.15
## # ... with 44,916 more rows, and 4 more variables: deaths_per_woman <dbl>,
## #   poverty <dbl>, education <dbl>, health_exp <dbl>
d <- select(death, everything())
rate <- child_mortality
rate %>% 
  filter(year >= 1957 & !is.na(continent)) %>%
  group_by(continent, year) %>% 
  summarise(child_mort = sum(child_mort, na.rm = TRUE)) %>% 
ggplot(aes(x = year, y = child_mort, color = continent)) +
    geom_point() +geom_line()+ facet_wrap(~continent,nrow=1)+
    theme_dark() + scale_color_manual(values = c("black","pink","gray","purple","violet"))+
    labs(
      title = "Child Mortality by Continent and by Year",
      x = "Year",
      y = "The Number of Children dying before the age of 5 years (per 1,000 births)"
    )
## `summarise()` regrouping output by 'continent' (override with `.groups` argument)

I am trying to reproduce a graph from []https://ourworldindata.org/child-mortality The graph shows how the number of deaths for children under 5 years has been changing between 1990 and 2017

data <- read.csv("C:/Users/exoni/Downloads/child-deaths-igme-data.csv")
da <- filter(data,Year>=1990)
dat <- da %>% group_by(Year) %>% summarise(World=sum(deaths))
## `summarise()` ungrouping output (override with `.groups` argument)
dat$World <- dat$World/1000000
P <- ggplot(dat)+geom_line(aes(Year,World),color="blue",size=1)+geom_point(aes(Year,World),color="blue",size=3)+labs(y= "Number of Deaths in the World(in millions)",title="Number of Child Death, 1990-2017. \n Number of Deaths of children under 5 years old.")+theme_bw()

ggplotly(P, tooltip=c("World","Year"),width = 1000, height = 600) %>%
    animation_opts(17)